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Keynote: Unexpected repurposing
- 1. Unexpected Repurposing: the British Library's digital collections and UCL teaching, research and infrastructure Professor Melissa Terras Professor of Digital Humanities, UCL Dept of Information Studies Director, UCL Centre for Digital Humanities m.terras@ucl.ac.uk, @melissaterras
- 4. #openglam
- 5. British Library, 28th May 2008. https://web.archive.org/web/20110707135434/http://pressandpolicy.bl.uk/Press-Releases/The-British-Library-19th-Century-Book-Digitisatio Returned to library in 2012, placed under a CCO-Public domain license for commercial and non-commercial use.
- 10. Optically Character Recognised (OCR) generated TextScanned Page
- 11. OCR XML Generated by ABBY Fine Reader
- 19. Data: what can we do with 65,000 books? 224GB compressed ALTO XML
- 23. Staff and Students, working together • James Baker, Adam Farquhar • Melissa Terras, Dean Mohamedally, Tim Weyrich, • Stefan Alborzpour, Stelios Georgiou, Nektaria Stavrou, Wendy Wong, Jonathan Lloyd, Meral Sahin, Divya Surendran, James Durrant, Muhammad Rafdi, Ali Sarraf
- 25. Approach • How can we search the dataset differently? • Complex and multifaceted needs of humanities researchers • Boolean and Advanced Search • Microsoft Azure 5 APIs were implemented that functionally scale to the data • Offering unconventional services such as bulk download of text based on metadata queries, word frequency lists, and OCR text previews.
- 32. picaguess.herokuapp.com, dx.doi.org/10.5281/zenodo.15980 James Baker, Tim Weyrich, Dean Mohamedally Jonathan Lloyd, Meral Sahin,Divya Surendran
- 33. http://blbigdata.herokuapp.com/ James Baker, Tim Weyrich, Dean Mohamedally, Ali Sarraf, James Durrant, Muhammad Rafdi
- 38. Method • 65k books from the British Library: • 17th - 19th century • 224GB compressed ALTO XML • UCL High Performance Computing • Support from RITS and UCLDH • 4 humanities researchers • Turn research questions into computational queries • Learn from the researchers about their needs, wants, desires, and method.
- 39. Results
- 40. Taking Humanities data to HPC… https://www.flickr.com/photos/epublicist/3546059144
- 42. Case Study 1: History of Medicine, Oliver Duke-Williams, UCL
- 43. Case Study 2: History of Images, Will Finley, Sheffield
- 44. What did this tell us? • Best practice recommendations: – Derived datasets for home use – Documentating decisions – Fixed/defined dataset – Normalisations
- 48. Common Queries • searches for all variants of a word • searches that return keywords in context traced over time • NOT searches for a word or phrase that ignored another word or phrase • searches for a word when in close proximity to a second word • searches based on image metadata …. All returned in a derived dataset, in context.
- 49. Do try this at home… 1. Invest in research software engineer capacity to deploy and maintain openly licensed largescale digital collections from across the GLAM sector in order to facilitate research in the arts, humanities and social and historical sciences 2. Invest in training library staff to run these initial queries in collaboration with humanities faculty, to support work with subsets of data that are produced, and to document and manage resulting code and derived data.
- 54. With thanks to • BL Labs and Digital Curators: James Baker, Adam Farquhar, Mahendra Mahey, Ben O’Steen, Hana Lewis • UCL CS Student Project Team: James Baker, Tim Weyrich, Dean Mohamedally • Bluclobber Project Team: James Baker, James Hetherington, David Beavan, Anne Welsh, Helen O’Neill, Will Finley, Oliver Duke-Williams, Adam Farquhar. • UCL Research IT Services: James Hetherington, Clare Gryce, Raquel Algere.
Editor's Notes
- Novel encounters
- Crowds and structured data generation